Browsing publications of the working group of computational biology for individualized medicine ([CiiM] BIIM) by Authors
COVID-19 immune signatures reveal stable antiviral T cell function despite declining humoral responses.Bonifacius, Agnes; Tischer-Zimmermann, Sabine; Dragon, Anna C; Gussarow, Daniel; Vogel, Alexander; Krettek, Ulrike; Gödecke, Nina; Yilmaz, Mustafa; Kraft, Anke R M; Hoeper, Marius M; et al.Cellular and humoral immunity to SARS-CoV-2 is critical to control primary infection and correlates with severity of disease. The role of SARS-CoV-2-specific T cell immunity, its relationship to antibodies, and pre-existing immunity against endemic coronaviruses (huCoV), which has been hypothesized to be protective, were investigated in 82 healthy donors (HDs), 204 recovered (RCs), and 92 active COVID-19 patients (ACs). ACs had high amounts of anti-SARS-CoV-2 nucleocapsid and spike IgG but lymphopenia and overall reduced antiviral T cell responses due to the inflammatory milieu, expression of inhibitory molecules (PD-1, Tim-3) as well as effector caspase-3, -7, and -8 activity in T cells. SARS-CoV-2-specific T cell immunity conferred by polyfunctional, mainly interferon-γ-secreting CD4+ T cells remained stable throughout convalescence, whereas humoral responses declined. Immune responses toward huCoV in RCs with mild disease and strong cellular SARS-CoV-2 T cell reactivity imply a protective role of pre-existing immunity against huCoV.
Pilot Study Using Machine Learning to Identify Immune Profiles for the Prediction of Early Virological Relapse After Stopping Nucleos(t)ide Analogues in HBeAg-Negative CHB.Wübbolding, Maximilian; Lopez Alfonso, Juan Carlos; Lin, Chun-Yen; Binder, Sebastian; Falk, Christine; Debarry, Jennifer; Gineste, Paul; Kraft, Anke R M; Chien, Rong-Nan; Maasoumy, Benjamin; et al. (Wiley, 2020-11-05)Treatment with nucleos(t)ide analogues (NAs) may be stopped after 1-3 years of hepatitis B virus DNA suppression in hepatitis B e antigen (HBeAg)-negative patients according to Asian Pacific Association for the Study of Liver and European Association for the Study of Liver guidelines. However, virological relapse (VR) occurs in most patients. We aimed to analyze soluble immune markers (SIMs) and use machine learning to identify SIM combinations as predictor for early VR after NA discontinuation. A validation cohort was used to verify the predictive power of the SIM combination. In a post hoc analysis of a prospective, multicenter therapeutic vaccination trial (ABX-203, NCT02249988), hepatitis B surface antigen, hepatitis B core antigen, and 47 SIMs were repeatedly determined before NA was stopped. Forty-three HBeAg-negative patients were included. To detect the highest predictive constellation of host and viral markers, a supervised machine learning approach was used. Data were validated in a different cohort of 49 patients treated with entecavir. VR (hepatitis B virus DNA ≥ 2,000 IU/mL) occurred in 27 patients. The predictive value for VR of single SIMs at the time of NA stop was best for interleukin (IL)-2, IL-17, and regulated on activation, normal T cell expressed and secreted (RANTES/CCL5) with a maximum area under the curve of 0.65. Hepatitis B core antigen had a higher predictive power than hepatitis B surface antigen but lower than the SIMs. A supervised machine-learning algorithm allowed a remarkable improvement of early relapse prediction in patients treated with entecavir. The combination of IL-2, monokine induced by interferon γ (MIG)/chemokine (C-C motif) ligand 9 (CCL9), RANTES/CCL5, stem cell factor (SCF), and TNF-related apoptosis-inducing ligand (TRAIL) was reliable in predicting VR (0.89; 95% confidence interval: 0.5-1.0) and showed viable results in the validation cohort (0.63; 0.1-0.99). Host immune markers such as SIMs appear to be underestimated in guiding treatment cessation in HBeAg-negative patients. Machine learning can help find predictive SIM patterns that allow a precise identification of patients particularly suitable for NA cessation.